An unsupervised CNN trained on MRI-PET pairs with SSIM loss produces fast fusions and a gradient-based color map of source contributions, but its main metric mirrors its training loss.
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Structural Similarity based Anatomical and Functional Brain Imaging Fusion
An unsupervised CNN trained on MRI-PET pairs with SSIM loss produces fast fusions and a gradient-based color map of source contributions, but its main metric mirrors its training loss.